Cooperative Scheduling for OMA NOMA Interference Minimization
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Solution Overview
Problem
Current 5G radio resource scheduling methods, such as OMA and NOMA, face challenges in supporting high-density IoT device connectivity due to interference issues, which lead to performance degradation, especially in dense deployments where existing schemes are not efficient in managing inter-cellular and intra-cellular interference effectively.
Innovation Solution
A novel method for interference minimizing cooperative scheduling of radio resources is introduced, which involves establishing communicative coupling with base stations, computing prospective channel interference, and generating a cooperative schedule to assign radio resource channels that minimize interference, supporting both OMA and NOMA communications by classifying UE into groups based on channel interference and optimizing power allocation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If OMA schemes are used for resource allocation, then orthogonality in radio resources is achieved, but the capacity to support massive IoT devices (more than fifty-thousand per base station) is insufficient
Solution Approach 1:
The patent combines OMA and NOMA schemes into a unified resource allocation framework. Base stations can dynamically select which scheme to apply to different user groups or resource blocks, merging the orthogonality benefits of OMA with the capacity benefits of NOMA to simultaneously support massive device connectivity while maintaining resource orthogonality where needed
Solution Approach 2:
The patent implements dynamic resource allocation where the scheduling scheme (OMA or NOMA) is not fixed but adapts based on channel conditions, device density, and traffic requirements. This dynamic selection allows the system to optimize between orthogonality and capacity support depending on real-time network conditions
2Productivity
If NOMA is used to superpose multiple devices in given radio resources, then device support capacity increases exponentially, but receiver complexity increases due to successive interference cancellation requirements
Solution Approach 1:
The patent applies NOMA selectively to specific user groups, resource blocks, or channel conditions rather than uniformly across all resources. By identifying users with similar channel conditions (local quality groups) and applying NOMA only within these groups, the system achieves capacity enhancement while limiting the complexity burden to specific receiver groups rather than all devices
Solution Approach 2:
The patent segments the user population into different groups based on channel conditions, device capabilities, and QoS requirements. Some groups receive NOMA allocation while others receive OMA allocation, dividing the complexity burden and allowing low-capability devices to avoid successive interference cancellation while still benefiting from overall system capacity enhancement
3Productivity
If radio resources are not well managed in dense deployments, then massive connectivity is achieved, but massive interference results in severe performance degradation
Solution Approach 1:
The patent implements feedback mechanisms where user equipment reports channel state information, interference measurements, and decoding success/failure to the base station. This feedback enables the base station to adjust power allocation, select appropriate users for NOMA superposition, and dynamically switch between OMA and NOMA schemes to maintain performance in dense deployments while managing interference
Solution Approach 2:
The patent dynamically changes key parameters including power allocation coefficients, resource block assignments, and scheme selection (OMA vs. NOMA) based on channel conditions and interference levels. By adjusting these parameters in response to network conditions, the system achieves high connectivity density while controlling interference through optimized resource allocation
Data Source
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AI summary
Interference minimizing cooperative scheduling of radio resources for orthogonal multiple access (OMA) and non-orthogonal multiple access (NOMA) wireless communications includes receiving from each of multiple different base stations a base station scheduling table scheduling associated UE and corresponding base station channel parameters for each one of the radio resource channels of the one of the base stations. The method additionally includes computing prospective channel interface for each one of the radio resource channels for different combinations of the associated UE and generating a cooperative schedule for the associated UE for each one of the different base stations, the cooperative schedule assigning a specific one of the radio resource channels minimizing the computed prospective channel interference. Finally, the method includes transmitting the cooperative schedule to each of the different base stations for use by the different base stations in assigning the associated UE to assigned ones of the radio resource channels.